Data Science

caret

Question 1
Marks : +2 | -2
Pass Ratio : 100%
Which of the following function can create the indices for time series type of splitting?
newTimeSlices
createTimeSlices
binTimeSlices
none of the mentioned
Explanation:
Rolling forecasting origin techniques are associated with time series type of splitting.
Question 2
Marks : +2 | -2
Pass Ratio : 100%
Which of the following function is a wrapper for different lattice plots to visualize the data?
levelplot
featurePlot
plotsample
none of the mentioned
Explanation:
featurePlot is used for data visualization in caret.
Question 3
Marks : +2 | -2
Pass Ratio : 100%
Which of the following can be used to impute data sets based only on information in the training set?
postProcess
preProcess
process
all of the mentioned
Explanation:
This can be done with K-nearest neighbors.
Question 4
Marks : +2 | -2
Pass Ratio : 100%
Point out the correct statement.
Asymptotics are used for inference usually
Caret includes several functions to pre-process the predictor data
The function dummyVars can be used to generate a complete set of dummy variables from one or more factors
All of the mentioned
Explanation:
The function dummyVars takes a formula and a data set and outputs an object that can be used to create the dummy variables using the predict method.
Question 5
Marks : +2 | -2
Pass Ratio : 100%
caret stands for classification and regression training.
True
False
Explanation:
The caret package is a set of functions that attempt to streamline the process for creating predictive models.
Question 6
Marks : +2 | -2
Pass Ratio : 100%
Which of the following model model include a backwards elimination feature selection routine?
MCV
MARS
MCRS
All of the mentioned
Explanation:
MARS stands for Multivariate Adaptive Regression Splines.
Question 7
Marks : +2 | -2
Pass Ratio : 100%
Which of the following function can be used to maximize the minimum dissimilarities?
sumDiss
minDiss
avgDiss
all of the mentioned
Explanation:
sumDiss can be used to maximize the total dissimilarities.
Question 8
Marks : +2 | -2
Pass Ratio : 100%
For most classification models, each predictor will have a separate variable importance for each class.
True
False
Explanation:
The exceptions are classification trees, bagged trees and boosted trees.
Question 9
Marks : +2 | -2
Pass Ratio : 100%
Which of the following can also be used to find new variables that are linear combinations of the original set with independent components?
ICA
SCA
PCA
None of the mentioned
Explanation:
ICA stands for independent component analysis.
Question 10
Marks : +2 | -2
Pass Ratio : 100%
Which of the following function tracks the changes in model statistics?
varImp
varImpTrack
findTrack
none of the mentioned
Explanation:
GCV change value can also be tracked.